Chemical Production Scheduling

Introduction:

Scheduling is a decision-making process that ensures optimum allocation of resources to various competing tasks while minimizing/maximizing certain objectives e.g.: Maximization of profit, minimization of cost, etc. In the case of chemical processes, production scheduling is used to determine important decisions regarding raw material procurement, task allocation to processing units, timing, and sequencing of tasks to be performed in each unit (batch processes) which satisfies certain objectives while ensuring maximum utilization of the available resources.   

Challenges in Chemical Production Scheduling: Chemical production scheduling presents several challenges that need to be addressed to achieve optimal results. Some of the key challenges include:

• Complexity: Chemical production processes are often complex, involving multiple interconnected production units, reactors, and equipment. Coordinating the operations of these units while considering different reaction times, equipment availability, and interdependencies can be highly challenging.

• Uncertainty: The chemical industry is susceptible to various uncertainties, such as fluctuating demand, supply chain disruptions, and unforeseen equipment failures. Scheduling must account for these uncertainties and incorporate flexibility to adapt to changing conditions while minimizing the impact on production efficiency.

• Resource Allocation: Efficiently allocating resources, such as equipment, raw materials, and personnel, is crucial for optimal production scheduling. Balancing the utilization of resources while considering their availability, capacity constraints, and maintenance requirements is a significant challenge.

Strategies for Optimal Chemical Production Scheduling: To address these challenges and achieve efficient chemical production scheduling, several strategies and techniques can be employed:

• Advanced Planning and Scheduling (APS) Systems: Implementing APS systems enables the optimization of production scheduling by considering multiple variables and constraints. These systems leverage mathematical algorithms and optimization techniques to generate schedules that minimize production costs, reduce changeovers, and maximize resource utilization.

• Collaboration and Communication: Effective communication and collaboration between various stakeholders, including production planners, operators, and supply chain partners, are vital for successful production scheduling. Sharing information about raw material availability, equipment maintenance schedules, and production priorities helps in making informed decisions and resolving scheduling conflicts.

• Simulation and Optimization Modeling: Utilizing simulation and optimization models enables the evaluation of different scheduling scenarios and the identification of optimal solutions. These models consider multiple variables, constraints, and objectives, helping to identify bottlenecks, optimize production sequences, and allocate resources efficiently.

Our objective is to formulate computationally efficient mixed integer programming models that represent the production complexities and develop advanced solution methods to address industrial scale problems in an efficient manner. 

The above figure is taken from: Misra, S., Maravelias, CT. Overview of Scheduling Methods for Pharmaceutical Production. In: Fytopoulos, A., Ramachandran, R., Pardalos, P.M. (eds) Optimization of Pharmaceutical Processes. Springer Optimization and Its Applications, 189, 355-371, 2022. Springer, Cham. https://doi.org/10.1007/978-3-030-90924-6_13

Relevant Research Articles from Group:

• Misra S, Buttazoni LR, Avadiappan V, Lee HJ, Yang M, Maravelias CT. CProS: A web-based application for chemical production scheduling. Computers & Chemical Engineering 164, 107895, 2022. https://doi.org/10.1016/j.compchemeng.2022.107895. 

• Misra S, Saxena D, Kapadi M, Gudi RD, Srihari R, Enclave Optimization: A Novel Multiplant Production Scheduling Approach for Cryogenic Air Separation Plants.  Industrial & Engineering Chemistry Research 57 (15), 5301-5322, 2018. https://doi.org/10.1021/acs.iecr.7b03235.

• Misra S, Gudi RD, Integration of Scheduling & Control for Sequential Batch Processes: An Iterative Approach, IFAC-PapersOnLine 51 (1), 84-89, 2018. https://doi.org/10.1016/j.ifacol.2018.05.015. 

• Misra S, Kapadi M, Gudi RD, Srihari R, Energy-efficient Production Scheduling of a Cryogenic Air Separation Plant. Industrial & Engineering Chemistry Research 56 (15), 4399-4414, 2017. https://doi.org/10.1021/acs.iecr.8b05138. 

• Misra S, Kapadi M, Gudi RD, Srihari R, Production scheduling of an air separation plant, IFAC-PapersOnLine 49 (7), 675-680, 2016. https://doi.org/10.1016/j.ifacol.2016.07.256.